Introduction to Computational Fluid Dynamics

Synopsis:

This introductory course is the first of the three-part series of courses which will prepare you for a career in the rapidly expanding field of computational fluid dynamics. Completion of these three courses will give you the equivalent of one semester of undergraduate and two semesters of graduate work. The courses are supported extensively with textbooks, computer programs, and user manuals. You can use the computer programs to develop your own code, or you may modify the existing code for assigned applications.

You will need access to a PC, FORTRAN compiler, and graphics package for the software applications. A fundamental knowledge of computer programming and familiarity with a basic graphic package are required.

How You Will Benefit From This Course:

Learn the terminology used in CFD.

Learn and experience how applications of various numerical schemes to scalar model partial differential equations are used to illustrate the different aspects of CFD.

Improve your understanding of the limitations and advantages of CFD.

Discover why CFD is the tool for fluid flow simulations and prediction that has virtually none of the inherent limitations of other simulation techniques.

Key Topics:

Classification of Partial Differential Equations (PDEs)

Finite-Difference Equations

Parabolic Equations

Stability Analysis

Elliptic Partial Differential Equations

Hyperbolic Partial Differential Equations

Scalar Representation of the Navier-Stokes Equations

Incompressible Navier-Stokes Equations

Who Should Attend:

This course is designed for engineers, scientists, and technical managers who are interested in learning the fundamentals and principles of CFD. The objectives of this course are to provide simple, but in-depth explanations of solution schemes. The content of this course is equivalent to one-semester course offered to upper level undergraduates or first year graduate students. Prior introductory courses in fluid mechanics and partial differential equations are also helpful.